As transistors shrink to nanoscale dimensions, trapped electrons--blocking "lanes" of electron traffic--are making it difficult for digital computers to work. In stark contrast, the brain works fine with single-lane nanoscale devices that are intermittently blocked (ion channels). Conjecturing that it achieves error-tolerance by combining analog dendritic computation with digital axonal communication, neuromorphic engineers (neuromorphs) began emulating dendrites with subthreshold analog circuits and axons with asynchronous digital circuits in the mid-1980s. Three decades in, researchers achieved a consequential scale with Neurogrid--the first neuromorphic system that has billions of synaptic connections. Researchers then tackled the challenge of mapping arbitrary computations onto neuromorphic chips in a manner robust to lanes intermittently--or even permanently--blocked by trapped electrons. Having demonstrated scalability and programmability, they now seek to encode continuous signals with spike trains in a manner that promises greater energy efficiency than all-analog or all-digital computing across a five-decade precision range.